Digital data and signal processing techniques and vision system technology have tremendously advanced the ability to use computers as data processing systems to accomplish sophisticated inspection procedures without human intervention. Almost every type of product can benefit from low cost, high precision, high-speed automated inspection technology derived from these new digital data and signal processing techniques.
One such situation that has greatly benefited from high-speed inspection technology involves material handling systems. For example, packages or parcels traveling on a conveyor belt must be spaced apart for individual tracking and tagging purposes. In this way, automated systems can duplicate tasks that were previously performed by humans, such as sorting parcels according to destination locations. However, in order for such automated material handling apparatus to operate efficiently and effectively, parcels must be aligned and spaced apart from each other as they travel on conveyor systems. If, on the other hand, parcels are side-by-side or overlap, then it is quite possible that one or more parcels will be erroneously sorted, which will result in at least one parcel arriving at an incorrect destination. As can be appreciated, such situations incur additional costs in shipping and time.
Accordingly, it would be advantageous to provide a system and method of identifying side-by-side and/or overlapped parcel conditions to eliminate as many erroneous delivery situations as possible. Advantageously, such a system would be automated such that the majority of parcel overlap conditions can be automatically detected without human intervention. Preferably, such a system would utilize machine vision cameras, illumination systems, machine vision processors (computers) and innovative image processing techniques to detect multiple object conditions, such as side-by-side and overlap parcels on a package conveyor.